At this point, there is no real question as to whether or not Earth’s language diversity is dwindling, as it already clearly is. But there is a question as to how much of this phenomenon is due to increasingly powerful machine translation (MT) tools such as neural machine translation (NMT) versus how much is due to natural processes.
What do Wordpress, Linux, and Firefox all have in common? All of these successful projects are the result of crowdsourced contributions. As the Internet continues to connect us, collaborating on projects has become easier than ever. Even in the localization industry, crowdsourced translation solutions are helping to make translation services available to everyone and the advent of new technologies has brought about a few different methods of collaborative translation projects. Let’s take a look at three of the most popular models of crowdsourced translations.
Advances in technology are constantly changing the way we live and, when it comes to translation, this is no different. Gone are the days of flipping through an old ‘Spanish to English’ dictionary, looking up every word in a sentence, and trying to form something that vaguely resembles a translation. Now it is much more common practice to just copy & paste the sentence into your favored machine translation service and instantly receive a more accurate and efficient result. These developments will continue to drastically change the future of translation, not just due to increasing levels of technology but also, through the emergence of platforms in which bilinguals around the world can contribute freely by translating pieces of text – crowdsourcing.
Translation memory is an important tool in the modern translator’s toolkit, and one that is currently the focus of a great deal of discussion in the translation and localization community. Simply put, translation memory is a type of shared database that stores translations and continually updates itself as its users work.